Abstract
Purpose
Low back pain (LBP) is the most prevalent public health problem globally, second only to headaches in the ranking of painful disorders that affect human beings. However, evidence about the profile of LBP patients is lacking in low-income countries for appropriate management approaches. This study examined the profile of individuals with LBP and factors defining chronicity of pain in Ethiopia.
Methods
A population-based cross-sectional study design was used to collect data from 1812 adults (≥ 18 years) with LBP at present. Data were collected by interviewing the study participants using an instrument developed and validated in the same study population. The instrument includes socio-demographic information, health behaviours/lifestyle habits, beliefs about pain, and pain and general health-related characteristics of the participants. Data analysis was performed using R version 3.5.1. Both unconditional and conditional logistic regression models were fitted and Odds Ratio (OR) with 95% confidence intervals (95% CIs) were computed to identify factors significantly associated with chronicity of pain at p ≤ 0.05 significance level.
Results
Negative beliefs about pain, a varying degree of pain interference with daily and social activities, complaining of pain in other anatomical sites other than the low back region, general health status rated as not excellent, depressive symptomology, and sleeping problems/insomnia were common within the profile of individuals with LBP. Age, educational level, residential setting, beliefs about pain, and depressive symptomology were found to have a statistically significant association with chronicity of pain.
Conclusions
This study provides an overview of the profile of individuals with LBP and factors defining chronicity of pain, assisting clinicians to design appropriate management strategies to improve patients' outcomes.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Low back pain (LBP) is pain localised below the line of the 12th rib and above the inferior gluteal folds, with or without leg pain [1, 2]. LBP is the most prevalent public health problem globally, second only to headaches in the ranking of painful disorders that affect human beings [3]. The pain can be either specific or non-specific, based on causal factors. Specific LBP is caused by known pathology, such as infection, osteoporosis, rheumatoid arthritis, fracture, or tumour [4], whereas non-specific LBP is not attributable to a recognisable, known specific pathology [4,5,6]. LBP can affect up to 80% of all individuals [7], and non-specific LBP shares approximately 90% of it [4, 5]. The most recent epidemiological data demonstrate that the annual global incidence of LBP is 245.9 million with an overall prevalence of 577 million and disability-adjust life years (DALYs) accounting for 64.9 million [8]. Evidence shows that an individual with LBP at a point in time will have a strong tendency towards having continuing pain or having it again [9]. Indeed, it has been proven to be a chronic disease [10], marked by a stable pattern of episodes, which may occur frequently or infrequently and these episodes may be of short or of long duration [11].
Studies have shown that a large proportion of people with chronic LBP also report mental health disturbances, such as elevated depressive and anxiety symptoms, as well as disability in activities of daily life[12,13,14]. These effects, in turn, are seen to worsen the experience of pain [13], suggesting complex relationships between pain, pain outcomes, and related quality of life. When measured using the 36-Item Short Form Survey (SF-36), an association between lower summary score (poor health-related quality of life) and LBP was seen [15], particularly among individuals with chronic LBP [2]. Socio-demographic variables such as older age [16, 17], and health behaviours/lifestyle habits such as obesity and lack of physical exercise [16] have also been reported as factors associated with increasing occurrence of poor health-related quality of life in people with LBP. Therefore, it is clear that LBP is a complex health condition with irregular and uncertain outcomes [18], and continues to be one of the most controversial and difficult health conditions to manage for clinicians, patients, and policy makers [19]. LBP, particularly when it moves to the chronic phase, and combined with other comorbid conditions, is known to have an array of negative health impacts, with significant, life-changing psychological and social consequences [20]. Effective management of pain in its early phase could be important to minimise the substantial burden of LBP [21, 22].
In Ethiopia, infectious diseases, such as tuberculosis, malaria, diarrhoeal diseases, HIV/AIDS, and lower respiratory infections, are the leading health issues. A study undertaken by Misganaw et al. [23] found that in 2015, the all-cause crude death rate was 680.9 (95% uncertainty interval (UI): 505.1–913.9) per 100,000 population. Of this, 337 (95% UI: 273.8–421.3) per 100,000 population and 286.9 (95% UI: 188.1–423.0) per 100,000 population death rates were caused by communicable and noncommunicable diseases, respectively. The same study further showed that HIV/AIDS and tuberculosis together caused 72.8 (95% UI: 50.9–101.0) deaths per 100,000 population. Diarrhoea, lower respiratory infections, and other common infectious diseases accounted for 147.4 (95% UI: 113.9–191.0) deaths per 100,000 population, while cardiovascular diseases and neoplasms accounted for 120.5 (95% UI: 77.1–177.5) and 55.6 (95% UI: 32.8–89.8) deaths per 100,000 population, respectively. Combined with these long-standing infectious diseases and other common noncommunicable diseases, the burden of LBP in Ethiopia may be large and amount to a considerable public health concern. However, there has been no study devoted to epidemiological data about the profile of individuals with LBP in Ethiopia to date, limiting the effectiveness of management strategies for improved outcomes. This study was therefore aimed to offer a detailed epidemiological information about the profile of individuals with LBP and factors associated with chronicity of pain in Ethiopia. The findings may assist to develop sensible and practical planning for appropriate pain management strategies and improved outcomes.
Methods
Study design and setting
A population-based cross-sectional study design was used to describe the profile of individuals with LBP, residing in South-west Shewa zone of Oromia regional state, located in central Ethiopia.
Sample size
A single population proportion formula was used to determine the study sample size. The calculation involved a 95% confidence level (Zα/2 = 1.96), and a low margin of error (d = 4%). The expected proportion of chronic LBP (p = 50%) was assumed, because of the absence of any previous study, and a design effect (DE) of 3 was also factored in considering a multi-stage sampling technique. In this way, a total of 1981 adults with LBP were included in the study with a 10% non-response rate [24].
Sampling procedure
A multi-stage sampling technique was used to select the study participants. Firstly, the districts in South-west Shewa zone were stratified into urban and rural. Three districts (one urban and two rural) were then selected as endorsed by Cohen et al. [25]. Finally, two wards were randomly picked from each of the three selected districts using the OpenEpi Random number generator [26], totalling six wards. The households within the selected wards were then selected proportionally using a systematic random sampling method. Important to note that while the households were the sampling units, the individuals with LBP (≥ 18 years of age) were the study units.
Data collection instrument
The instrument used in this study was first developed and validated in the same study population as described elsewhere [27]. The findings of the validation showed that the instrument is both valid and reliable to measure the profile of individuals with LBP. The instrument covers items measuring socio-demographic characteristics, health behaviours/lifestyle habits, and pain and general health-related profile of individuals with LBP (Supplementary materials). Socio-demographic factors such as gender, age, ethnicity, educational level, residence, marital status, and living conditions were included in the instrument. To measure health behaviours/lifestyle habits, information about smoking (smoking status, duration of smoking, and number of cigarettes smoked per day), alcohol consumption status and frequency of consumption, and khat chewing status and frequency of chewing were collected. Beliefs about pain were measured with a five-item scale, with response options ranging from strongly agree to strongly disagree. Optimistic individuals who scored above the mean were rated as having positive beliefs, while those scored below the mean score were rated as having negative beliefs. Information about intensity of pain (measured on a 10-point Numerical Rating Scale [NRS]), duration since pain onsets, pain interference with daily and social activities, whether pain spreads down the leg(s) or not and whether it caused time off work or not, number of days off work due to pain, and whether pain present in other anatomical sites other than the low back region or not were included in the instrument to assess pain-related profile of individual participants. General health-related information such as self-rated general health status and the presence of depressive symptomology and sleeping problems/insomnia were also covered in the instrument. The specific methods used to measure and define the variables such as intensity of pain, depressive symptomology, and insomnia have been described elsewhere [24].
Data collection
The data were collected by graduates with a First degree in health and/or a related field (n = 12), who were familiar with the culture, norms, and language of the local communities, but who did not know the families in the study area. For each ward, two data collectors were assigned, and collected the data by interviewing individuals with LBP using the Oromo language version of the instrument. In identifying cases with LBP, the individuals were directed to a picture of a person with a shaded area defining the low back region and were asked whether they had pain lasting more than one day in that region. Individuals were defined as having LBP and invited to be included in the study if they reported that they had pain in the specified body region. Only one adult with LBP was interviewed from each of the selected households. Whenever two or more eligible respondents were found in the selected household, only one respondent was chosen by the lottery method. With this method, each of the individuals with LBP was assigned a unique number, which was placed in a bowl, from which only one of the numbers was drawn at random. Where there was no eligible interviewee in the selected household, the next household was visited.
Statistical analysis
The data were analysed using R version 3.5.1. To provide insight into the profile of individuals with LBP, descriptive analyses were carried out and the findings were presented as frequency, percentage, median interquartile range (IQR), table, and graph. Defining chronic LBP as pain lasting for more than 3-month [28, 29], both unconditional and conditional logistic regression models were also fitted and Odds Ratio (OR) with 95% confidence intervals (95% CIs) were computed to identify factors statistically associated with chronicity of LBP at p ≤ 0.05 significance level. The predicting factors included in the models were gender, age, educational level, residence, marital status, living conditions, smoking, alcohol consumption, khat chewing, beliefs about pain, pain interference with daily and social activities, intensity of pain, the presence of pain in other anatomical sites other than the low back region, depressive symptomatology, sleeping problems/insomnia, and self-rated general health status. Chronicity of pain was the only dependent variable included in the models.
The association between each predicting factor and chronicity of pain was first assessed independently using an unconditional logistic regression model. However, this model could not account for the effects of confounding factors and yields only crude OR with 95% CIs and p values. For this reason, conditional logistic regression model, where each predicting factor was matched with age and depressive symptomology, was then fitted to determine AOR with 95% CIs and p values. This helped to identify the true association between each predicting factor and chronicity of pain.
Results
Socio-demographic profile
Of the total 1981 approached individuals with a self-reported history of LBP, 1812 participated in this study, making a response rate of 91.5%. The proportion of males was slightly higher than females (984 [54.3%] vs. 828 [45.7%]). The median (IQR) of participants' age was 38 (30–50) years. The details of socio-demographic characteristics of the study participants are presented elsewhere [24].
Health behaviours/lifestyle habits and beliefs about pain
Unhealthy behaviours such as substance use (smoking, alcohol consumption, and khat chewing) were uncommon. For example, only 58 (3.2%) of individuals with LBP were smokers with median (IQR) years of smoking 5.5 (2.75–10). Similarly, only 154 (8.5%) were khat chewers at the time of data collection. About 47% of the participants had negative beliefs about pain (Table 1).
Pain-related profile
Apart from 412 (22.7%), the remaining 1400 (77.3%) participants reported a varying degree of pain that interfered with their daily activities, ranging from a little bit to very much. In 542 (29.9%) people, time off work caused by pain was identified. Table 2 presents the details of pain-related characteristics of individuals with LBP.
Pain in the upper back region was a common attendant of LBP. Of 463 (25.6%) complaints of pain in other anatomical sites other than the low back region, the majority, 278 (60%) reported pain in the upper back region, while 72 (15.6%) indicated pain in the shoulder area (Fig. 1).
General health-related profile
More than a quarter (25.7%) of individuals with LBP indicated that they had sleeping problems/insomnia. Self-reported general health status of fair and poor were reported by 307 (17%) and 66 (3.6%) of the participants, respectively (Table 3).
Factors associated with chronicity of pain
In the unconditional logistic regression model, socio-demographic factors (such as age, educational level, marital status, residence, and living conditions), behavioural factors (such as alcohol consumption status and beliefs about pain), and clinical factors (such as depressive symptomology) were found to be associated with chronicity of LBP. However, when adjusting for age and depressive symptomology in the conditional logistic regression model, only age, educational status, residence, beliefs about pain, and depressive symptomology remained as having a statistically significant association with chronicity of LBP.
Increasing age group from 18–29 years was associated with increasing odds of having chronic LBP (30–39 years, AOR = 1.77, 95% CI 1.33–2.35; 40–49 years, AOR = 3.12, 95% CI 2.21–4.46; ≥ 50 years, AOR = 6.84, 95% CI 4.64–10.32). Alternatively, when age was fitted in the unconditional logistic regression model as a continuous variable, for each one-year increase in age, chronicity of LBP also observed to increase by 1.06-factor (AOR = 1.06, 95% CI 1.04 – 1.07, and p < 0.001). When compared with individuals who did not attend formal education, those who attended grade 1–8, grade 9–12, and those who graduated technical/vocational certificate, diploma, and degree or higher were found to have a higher prevalence of chronic LBP. Thus, those who attended grade 1–8 (AOR = 1.91, 95% CI 1.29–2.81) and grade 9–12 (AOR = 3.00, 95% CI 1.91–4.73) were 1.91 and 3 times more likely to have chronic LBP than those who did not attend formal education, respectively. Similarly, graduates of technical/vocational certificate (AOR = 2.35, 95% CI 1.36–4.11), diploma (AOR = 2.67, 95% CI 1.63–4.41), and degree or higher (AOR = 3.16, 95% CI 1.85–5.51) were 2.35, 2.67, and 3.16 times more likely to report a history of chronic LBP than their counterparts, respectively. In rural residents, the odds of reporting chronic LBP were 65% lower compared with their urban counterparts (AOR = 0.35, 95% CI 0.27–0.46).
There was also a statistically significant association between individuals' beliefs about pain and chronicity of pain. Those who had positive beliefs about pain were 33% less likely to have chronic LBP than individuals who had negative beliefs of pain (AOR = 0.67, 95% CI 0.52–0.85). In addition, a statistically significant association was observed between depressive symptomology and chronicity of pain. Compared with individuals who had no depressive symptomology, those who were at the borderline of depressive symptomology were 2.23 time more likely to have chronic LBP (AOR = 2.23, 95% CI 1.69–2.97), while those who had depressive symptomology were 1.95 times more likely (AOR = 1.96, 95% CI 1.33–2.96) (Table 4).
Discussion
This study aimed to offer the first epidemiological information about the profile of individuals with LBP and factors defining chronicity of pain using a representative sample of individuals with LBP from both urban and rural settings in Ethiopia. The study identified socio-demographic characteristics, lifestyle habits, beliefs about pain, and pain and general health-related characteristics of these individuals. The study also identified statistically significant factors associated with chronicity of LBP. These included age, educational level, residence, beliefs about pain, and depressive symptomology.
Profiles reflecting individuals with LBP
The most common pain-related characteristics identified in this study included pain interfering with daily and social activities to a varying degree, ranging from a little bit to very much, time off work due to pain, intensity of pain ranging from mild to severe, and comorbidity with other spinal pain. When LBP is classified as acute (lasts < 4 weeks), subacute (lasts 4–12 weeks), and chronic (lasts > 12 weeks), 79.4% of participants classified their pain as chronic. A considerable proportion of people with LBP were also found to have negative beliefs about pain (for example, believing that the pain makes everything in life worse and healthcare providers cannot do anything to assist the pain). In addition, depressive symptomology, sleeping problems/insomnia, and unfavourable general health status (i.e., general health status that was not excellent when self-rated) were also among the common profiles reflecting individuals with LBP. In general, these findings are comparable with the findings of a study that described the profile of patients with acute LBP seeking emergency departments in public hospitals in Brazil [30]. In that study, a significant proportion of patients with LBP were identified to have pain spreading down the leg(s), higher intensity of pain, 1-week lasting disability caused by pain, self-rated general health status of good, and psychological interference including stress, anxiety, and depression. The same study also showed that most patients with LBP were overweight with a low level of physical activity. However, body mass index (BMI) level and physical activity level were not presented in this study due to the items measuring them not meeting the factor extraction criteria (and were removed) when carrying out factor analysis to validate the data collection instrument. Several other studies [31,32,33,34] also reported that people with LBP complain about sleeping problems/insomnia, which is consistent with the current study. Uchmanowicz et al. [35] further described sleeping problems/insomnia as a statistically significant factor affecting quality of life in people with LBP and called for public health intervention.
Socio-demographic factors associated with chronicity of LBP
Three socio-demographic factors, namely, age, educational level, and residential setting, were identified to have a statistically significant association with chronicity of LBP. There was a gradual and proportional increase in chronicity of pain with increasing age, which is similar to the findings of previous studies [36, 37]. Malta et al. [36] linked this dose–response association between age and chronicity of LBP with the changes in the body because of the ageing process, such as postural problems, decreased flexibility, and increased musculoskeletal degeneration, which give rise to exacerbation of pain.
Previous studies reported an inverse association between educational level and occurrence of chronic LBP [36, 38,39,40]. In those studies, lower educational level was found to increase occurrence of chronic LBP, and scholars argued that less schooling population often engaged in more strenuous work and physically demanding jobs, and reduced access to healthcare [36]. The findings of the present study, however, showed improved educational level as increasing the risk of chronic LBP. Regular physical exercise is demonstrated to have a significant role in the management of LBP [41, 42]. However, there is an argument that due to lack of access to transportation systems and poorer income, individuals with lower educational level may be involved in some beneficial physical activities, such as walking more commonly when compared with individuals with improved educational level [43]. Thus, the reason why people with improved educational level had a higher odds of reporting chronic LBP in this study could be associated with this argument.
A study investigated factors predicting occurrence of chronic LBP in Brazilian adults [36] found that the proportion of chronic LBP was higher in males living in rural than urban settings for unexplained reasons. An incongruent result was observed in this study, as those living in rural areas were found to have 65% lower odds of having chronic LBP than their counterparts living in urban areas. In a previous paper [24], it was reported that the proportion ratio of healthcare utilisation for optimal management of LBP was higher in rural than urban populations (adjusted proportion ratio = 1.69, 95% CI 1.44–1.99). Thus, the lower odds of chronic LBP in the rural population may be linked with the higher rate of healthcare utilisation in the rural population, which improves their pain conditions and halts the progression of pain to the chronic phase.
There is evidence that individuals with unhealthy lifestyles, such as smoking cigarettes, have a higher predisposition to develop chronic pain, because nicotine could lead to an activation of the immune system and predispose people with a history of smoking to LBP, rheumatic diseases, and other health conditions [39, 44]. In terms of chronicity of pain, evidence is lacking to demonstrate the association between unhealthy lifestyles and LBP. The findings of the current study also did not find a statistically significant association between chronicity of LBP and unhealthy lifestyles, including smoking and chewing khat, except that alcohol intake was marginally associated increased chronicity of pain.
Psychological factors associated with chronicity of LBP
According to Teixeira et al. [45], patients' and healthcare providers' negative attitudes and beliefs about pain reduce the capacity of patients to cope with painful symptoms, leading to adoption of passive treatment strategies, such as the biomedical model of care that may present a high risk of persistence of pain and disability [46, 47]. In contrast, positive attitudes and beliefs about LBP were argued to be important factors for prevention of pain persistence and disability. The findings of this study supported this claim and showed a protective effect of positive beliefs on chronicity of LBP. Individuals who with positive beliefs about their pain had 33% less chance of reporting chronic LBP, when compared with those with negative beliefs.
In a systematic review of psychological factors predicting chronicity/disability in LBP patients, depressive mood, distress, and somatisation were shown to be associated with the transition of pain from acute presentation to chronic phase [48]. This study also found a strong association between depressive symptomology and chronicity of LBP. The odds of having chronic LBP were higher in individuals who had depressive symptomology and at the borderline for those who had not. For this reason, Pincus et al. [48] indicated the need for the development and testing of clinical interventions targeting these psychological factors in particular.
Strengths and limitations of the study
The strengths of this study include being a population-based study with a large sample from a socio-economically diverse and representative population. To the best of the authors' knowledge, this is the first ever epidemiological information about the profile of individuals with LBP and factors defining chronicity of pain in Ethiopia. However, the study has some limitations, including possibility of acquiescence response bias, where the respondents agree with the statements regardless of their contents [49]. Such bias may affect validity of the results and lead to wrong conclusions. The literature argues that the extent of occurrence of acquiescence response bias in a survey research ranges from 10 to 20% [50]. In addition, provided the subjective nature of the participants' responses, the addition of alternative scales such as the Visual Analog Scale (VAS) might be helpful for a better understanding of how the individual participants rate their pain. However, this study missed such strategy for improved results. This study may also inherit the limitations of cross-sectional study design, such as the possibility of reverse causality between the reported predicting factors and chronicity of LBP.
Conclusions
This study provides an overview of the profile of individuals with LBP, including insights into multiple factors associated with chronicity of pain in a representative sample of people in Ethiopia as a sub-Saharan African country. In this population, chronic LBP was found to be a multifactorial biopsychosocial condition with age, educational level, residence, beliefs about pain, and depressive symptomology. Thus, integrating the profile of individuals with LBP and factors associated with chronicity of pain into pain management strategies and future interventions may help to improve patients' outcomes. Future longitudinal studies may also be needed to understand better the true directionality of the association between the identified predicting factors and chronicity of pain and to establish the relationship between chronicity of pain and functionality.
Data availability
The data for this study will be made available in the University of Tasmania data repository.
References
Chou, R., Qaseem, A., Snow, V., Casey, D., Cross, J. T., Shekelle, P., et al. (2007). Diagnosis and treatment of low back pain: A joint clinical practice guideline from the American college of physicians and the American pain society. Annals of Internal Medicine, 147(7), 478–491. https://doi.org/10.7326/0003-4819-147-7-200710020-00006
Shim, J.-H., Lee, K.-S., Yoon, S.-Y., Lee, C.-H., Doh, J.-W., & Bae, H.-G. (2014). Chronic low back pain in young Korean urban males: The life-time prevalence and its impact on health related quality of life. Journal of Korean Neurosurgical Society, 56(6), 482–487. https://doi.org/10.3340/jkns.2014.56.6.482
Helfenstein Junior, M., Goldenfum, M. A., & Siena, C. (2010). Occupational low back pain. Revista da Associação Médica Brasileira, 56(5), 583–589. https://doi.org/10.1590/S0104-42302010000500022
Koes, B., Van Tulder, M., & Thomas, S. (2006). Diagnosis and treatment of low back pain. British Medical Journal, 332(7555), 1430–1434. https://doi.org/10.1136/bmj.332.7555.1430
Balagué, F., Mannion, A. F., Pellisé, F., & Cedraschi, C. (2012). Non-specific low back pain. The Lancet, 379(9814), 482–491. https://doi.org/10.1016/s0140-6736(11)60610-7
van Tulder, M., Becker, A., Bekkering, T., Breen, A., Gil del Real, M. T., Hutchinson, A., et al. (2006). European guidelines for the management of acute nonspecific low back pain in primary care. European Spine Journal, 15(Suppl. 2), s169–s191. https://doi.org/10.1007/s00586-006-1071-2
Henry, S. M., Van Dillen, L. R., Ouellette-Morton, R. H., Hitt, J. R., Lomond, K. V., DeSarno, M. J., et al. (2014). Outcomes are not different for patient-matched versus nonmatched treatment in subjects with chronic recurrent low back pain: A randomized clinical trial. The Spine Journal, 14(12), 2799–2810. https://doi.org/10.1016/j.spinee.2014.03.024
Mattiuzzi, C., Lippi, G., & Bovo, C. (2020). Current epidemiology of low back pain. Journal of Hospital Management and Health Policy, 4, 15. https://doi.org/10.21037/jhmhp-20-17
Beaudet, N., Courteau, J., Sarret, P., & Vanasse, A. (2013). Prevalence of claims-based recurrent low back pain in a Canadian population: A secondary analysis of an administrative database. BMC Musculoskeletal Disorders, 14(1), 151. https://doi.org/10.1186/1471-2474-14-151
Fritz, J. M., Cleland, J. A., & Childs, J. D. (2007). Subgrouping patients with low back pain: Evolution of a classification approach to physical therapy. Journal of Orthopaedic & Sports Physical Therapy, 37(6), 290–302. https://doi.org/10.2519/jospt.2007.2498
Stanton, T. R., Fritz, J. M., Hancock, M. J., Latimer, J., Maher, C. G., Wand, B. M., et al. (2011). Evaluation of a treatment-based classification algorithm for low back pain: A cross-sectional study. Physical Therapy, 91(4), 496–509. https://doi.org/10.2522/ptj.20100272
Misiak, B., & Snarska, K. K. (2014). Quality of life of patients with back pain. The Journal of Neurological and Neurosurgical Nursing, 3(3), 107–115. https://doi.org/10.15225/PNN.2014.3.3.2
Bener, A., Verjee, M., Dafeeah, E. E., Falah, O., Al-Juhaishi, T., Schlogl, J., et al. (2013). Psychological factors: Anxiety, depression, and somatization symptoms in low back pain patients. Journal of Pain Research, 6(1), 95–101. https://doi.org/10.2147/JPR.S40740
Bener, A., Dafeeah, E. E., & Salem, M. O. (2015). Determinants of depression and somatisation symptoms in low back pain patients and its treatment: Global burden of diseases. Journal of the Pakistan Medical Association, 65(5), 473–479.
Bener, A., El-Rufaie, O. F., Kamran, S., Georgievski, A. B., Farooq, A., & Rysavy, M. (2006). Disability, depression and somatization in a low back pain population. APLAR Journal of Rheumatology, 9(3), 257–263. https://doi.org/10.1111/j.1479-8077.2006.00210.x
Woolf, A. D., & Pfleger, B. (2003). Burden of major musculoskeletal conditions. Bulletin of the World Health Organization, 81(9), 646–656.
Hicks, G. E., Gaines, J. M., Shardell, M., & Simonsick, E. M. (2008). Associations of back and leg pain with health status and functional capacity of older adults: Findings from the retirement community back pain study. Arthritis & Rheumatism, 59(9), 1306–1313. https://doi.org/10.1002/art.24006
Gregg, C., McIntosh, G., Hall, H., & Hoffman, C. (2014). Prognostic factors associated with low back pain outcomes. Journal of Primary Health Care, 6(1), 23–30. https://doi.org/10.1071/HC14023
Manchikanti, L., Singh, V., Falco, F. J., Benyamin, R. M., & Hirsch, J. A. (2014). Epidemiology of low back pain in adults. Neuromodulation Technology at the Neural Interface, 17(2), 3–10. https://doi.org/10.1111/ner.12018
Froud, R., Patterson, S., Eldridge, S., Seale, C., Pincus, T., Rajendran, D., et al. (2014). A systematic review and meta-synthesis of the impact of low back pain on people’s lives. BMC Musculoskeletal Disorders, 15(1), 50. https://doi.org/10.1186/1471-2474-15-50
Traeger, A., Henschke, N., Hübscher, M., Williams, C. M., Kamper, S. J., Maher, C. G., et al. (2015). Development and validation of a screening tool to predict the risk of chronic low back pain in patients presenting with acute low back pain: A study protocol. British Medical Journal Open, 5(7), e007916. https://doi.org/10.1136/bmjopen-2015-007916
Krismer, M., & Van Tulder, M. (2007). Low back pain (non-specific). Best Practice & Research Clinical Rheumatology, 21(1), 77–91. https://doi.org/10.1016/j.berh.2006.08.004
Misganaw, A., Haregu, T. N., Deribe, K., Tessema, G. A., Deribew, A., Melaku, Y. A., et al. (2017). National mortality burden due to communicable, non-communicable, and other diseases in Ethiopia, 1990–2015: Findings from the Global Burden of Disease Study 2015. Population Health Metrics, 15(1), 29. https://doi.org/10.1186/s12963-017-0145-1
Beyera, G. K., O’Brien, J., & Campbell, S. (2020). Determinants of health care utilisation for low back pain: A population-based study in Ethiopia. Health & Social Care in the Community, 28(3), 1058–1070. https://doi.org/10.1111/hsc.12939
Cohen, L., Manion, L., & Morrison, K. (2007). Research methods in education (6th ed.). Taylor & Francis.
OpenEpi: Open source epidemiologic statistics for public health, version 3.01 [http://www.openepi.com/Menu/OE_Menu.htm]
Beyera, G. K., O’Brien, J., & Campbell, S. (2020). The development and validation of a measurement instrument to investigate determinants of health care utilisation for low back pain in Ethiopia. PLoS ONE, 15(1), e0227801. https://doi.org/10.1371/journal.pone.0227801
Qaseem, A., Wilt, T. J., McLean, R. M., & Forciea, M. A. (2017). Noninvasive treatments for acute, subacute, and chronic low back pain: A clinical practice guideline from the American College of Physicians. Annals of internal medicine, 166(7), 514–530. https://doi.org/10.7326/M16-2367
Ramond-Roquin, A., Pecquenard, F., Schers, H., Van Weel, C., Oskam, S., & Van Boven, K. (2015). Psychosocial, musculoskeletal and somatoform comorbidity in patients with chronic low back pain: Original results from the Dutch transition project. Family Practice, 32(3), 297–304. https://doi.org/10.1093/fampra/cmv027
Oliveira, I. S., Vanin, A. A., Costa, L. O. P., Medeiros, F. C., Oshima, R. K. A., Inácio, A. A., et al. (2020). Profile of patients with acute low back pain who sought emergency departments: A cross-sectional study. Spine, 45(5), E296–E303. https://doi.org/10.1097/BRS.0000000000003253
Choi, Y. S., Kim, D. J., Lee, K. Y., Park, Y. S., Cho, K. J., Lee, J. H., et al. (2014). How does chronic back pain influence quality of life in Koreans: A cross-sectional study. Asian Spine Journal, 8(3), 346–352. https://doi.org/10.4184/asj.2014.8.3.346
Sribastav, S. S., Peiheng, H., Jun, L., Zemin, L., Fuxin, W., Jianru, W., et al. (2017). Interplay among pain intensity, sleep disturbance and emotion in patients with non-specific low back pain. PeerJ, 5, e3282. https://doi.org/10.7717/peerj.3282
Wang, H.-Y., Fu, T.-S., Hsu, S.-C., & Hung, C.-I. (2016). Association of depression with sleep quality might be greater than that of pain intensity among outpatients with chronic low back pain. Neuropsychiatric Disease and Treatment, 12, 1993–1998. https://doi.org/10.2147/NDT.S110162
Murase, K., Tabara, Y., Ito, H., Kobayashi, M., Takahashi, Y., Setoh, K., et al. (2015). Knee pain and low back pain additively disturb sleep in the general population: A cross-sectional analysis of the Nagahama study. PLoS ONE, 10(10), e0140058. https://doi.org/10.1371/journal.pone.0140058
Uchmanowicz, I., Kołtuniuk, A., Stępień, A., Uchmanowicz, B., & Rosińczuk, J. (2019). The influence of sleep disorders on the quality of life in patients with chronic low back pain. Scandinavian Journal of Caring Sciences, 33(1), 119–127. https://doi.org/10.1111/scs.12610
Malta, D. C., Oliveira, M. M. D., Andrade, S. S. C. D. A., Caiaffa, W. T., Souza, M. D. F. M. D., & Bernal, R. T. I. (2017). Factors associated with chronic back pain in adults in Brazil. Revista de Saúde Pública, 51(1), 9. https://doi.org/10.1590/S1518-8787.2017051000052
Oliveira, CVd. A., Souza, DEd., Magalhães, A. G., Silva, J. PCd., & Correia, G. N. (2020). Prevalence and factors associated with chronic back problem in women of childbearing age. Ciencia & Saude Coletiva, 25(3), 1041–1049. https://doi.org/10.1590/1413-81232020253.15522018
Smith, B. H., Elliott, A. M., Chambers, W. A., Smith, W. C., Hannaford, P. C., & Penny, K. (2001). The impact of chronic pain in the community. Family Practice, 18(3), 292–299. https://doi.org/10.1093/fampra/18.3.292
Webb, R., Brammah, T., Lunt, M., Urwin, M., Allison, T., & Symmons, D. (2003). Prevalence and predictors of intense, chronic, and disabling neck and back pain in the UK general population. Spine, 28(11), 1195–1202. https://doi.org/10.1097/01.BRS.0000067430.49169.01
Lindell, O., Johansson, S.-E., & Strender, L.-E. (2010). Living conditions, including life style, in primary-care patients with nonacute, nonspecific spinal pain compared with a population-based sample: A cross-sectional study. Clinical Epidemiology, 2, 261–271. https://doi.org/10.2147/CLEP.S14761
Alnaami, I., Awadalla, N. J., Alkhairy, M., Alburidy, S., Alqarni, A., Algarni, A., et al. (2019). Prevalence and factors associated with low back pain among health care workers in southwestern Saudi Arabia. BMC Musculoskeletal Disorders, 20, 56. https://doi.org/10.1186/s12891-019-2431-5
Tanishima, S., Hagino, H., Matsumoto, H., Tanimura, C., & Nagashima, H. (2020). The risk factor of worsening low back pain in older adults living in a local area of Japan: The GAINA Study. Yonago Acta Medica, 63(4), 319–325. https://doi.org/10.33160/yam.2020.11.017
Karunanayake, A. L., Pathmeswaran, A., Kasturiratne, A., & Wijeyaratne, L. S. (2013). Risk factors for chronic low back pain in a sample of suburban S ri L ankan adult males. International Journal of Rheumatic Diseases, 16(2), 203–210. https://doi.org/10.1111/1756-185X.12060
Wijnhoven, H. A., de Vet, H. C., & Picavet, H. S. J. (2006). Explaining sex differences in chronic musculoskeletal pain in a general population. Pain, 124(1–2), 158–166. https://doi.org/10.1016/j.pain.2006.04.012
Teixeira, L. F., Pereira, L. S., Silva, S. L., Dias, J., & Dias, R. C. (2016). Factors associated with attitudes and beliefs of elders with acute low back pain: Data from the study Back Complaints in the Elders (BACE). Brazilian Journal of Physical Therapy, 20(6), 553–560. https://doi.org/10.1590/bjpt-rbf.2014.0188
Darlow, B., Fullen, B. M., Dean, S., Hurley, D. A., Baxter, G. D., & Dowell, A. (2012). The association between health care professional attitudes and beliefs and the attitudes and beliefs, clinical management, and outcomes of patients with low back pain: A systematic review. European Journal of Pain, 16(1), 3–17. https://doi.org/10.1016/j.ejpain.2011.06.006
Ng, S. K., Cicuttini, F. M., Wang, Y., Wluka, A. E., Fitzgibbon, B., & Urquhart, D. M. (2017). Negative beliefs about low back pain are associated with persistent high intensity low back pain. Psychology, Health & Medicine, 22(7), 790–799. https://doi.org/10.1080/13548506.2016.1220602
Pincus, T., Burton, A. K., Vogel, S., & Field, A. P. (2002). A systematic review of psychological factors as predictors of chronicity/disability in prospective cohorts of low back pain. Spine, 27(5), E109–E120.
Holbrook A. Acquiescence Response Bias. In: Encyclopedia of Survey Research Methods. edn. Edited by Lavrakas PJ. Thousand Oaks: Sage Publications, Inc; 2011. https://doi.org/10.4135/9781412963947
Kuru, O., & Pasek, J. (2016). Improving social media measurement in surveys: Avoiding acquiescence bias in Facebook research. Computers in Human Behavior, 57, 82–92. https://doi.org/10.1016/j.chb.2015.12.008
Acknowledgements
We would like to thank the study participants and data collectors.
Funding
Open Access funding enabled and organized by CAUL and its Member Institutions. There are no financial disclosures to be reported for this study.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflicts of interest.
Ethical approval
Ethical approval for this study was obtained from the Human Research Ethics Committee (Tasmania) Network, ethics reference number H0017128. Approval for data collection was obtained from Oromia Regional State Health Bureau, the South-west Shewa Zone Health Office, and Health Officials of the selected districts.
Consent to participate
Verbal informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Beyera, G.K., O’Brien, J. & Campbell, S. Profile of individuals with low back pain and factors defining chronicity of pain: a population-based study in Ethiopia. Qual Life Res 31, 2645–2654 (2022). https://doi.org/10.1007/s11136-022-03148-5
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-022-03148-5